Manesh Murali
COO / Co-founder
parabole.ai
Parabole.ai offers a causal AI platform, TRA_I_N, that integrates IT and operational technology data to optimize multi-functional challenges in industries such as manufacturing and oil & gas. By applying causal theory, the platform enables enterprises to understand the underlying reasons for issues, leading to measurable improvements like a 10% reduction in procurement costs and enhanced energy efficiency.
- Artificial Intelligence
- Data & Analytics
- Enterprise Software
- Industrial Automation
- Software Only
Updated 7 months ago
Funding
Raised to date
$3.8MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Enterprises in manufacturing, oil & gas, and similar sectors face challenges in optimizing complex, multi-functional processes due to the difficulty in understanding the underlying causal relationships within their IT and operational technology (OT) data. Traditional data science methods often focus on correlations rather than causation, limiting the ability to identify the root causes of inefficiencies and implement effective solutions. This can lead to suboptimal decision-making and missed opportunities for improvement.
Solution
Parabole.ai offers TRA_I_N, a causal AI platform designed to integrate IT and OT data and apply causal theory to solve multi-functional optimization challenges. Unlike traditional AI approaches that focus on correlation, TRA_I_N enables enterprises to understand the "why" behind process behaviors, leading to more effective interventions. The platform blends subject matter expert knowledge with available data to address data quality gaps and generate ontologies and causal models. By identifying causal relationships, TRA_I_N helps companies achieve Pareto efficiency, balancing conflicting objectives to optimize outcomes such as procurement costs, energy consumption, and asset performance.
Target Audience
The primary target audience includes enterprises in manufacturing, oil & gas, chemical, and pharmaceutical industries seeking to optimize complex processes and improve decision-making through causal AI.
Features
- No-code system for rapid ontology and causal model generation, enabling both data scientists and non-developers to participate in AI modeling.
- Ability to blend subject matter expertise with available data, compensating for data quality gaps.
- Pre-built solution templates for efficient scaling across multiple use cases.
- Causal AI agents for procurement planning and optimization, touchless order processing, energy optimization, pipeline leakage detection, asset performance monitoring, and more.
- Integration with Microsoft Azure and Oracle marketplace for streamlined procurement.
- Support for multi-objective optimization, balancing conflicting objectives to achieve superior outcomes.